High-resolution global maps of 21st-century forest cover change MC Hansen, PV Potapov, R Moore, M Hancher, SA Turubanova, ... science 342 (6160), 850-853, 2013 | 11699 | 2013 |
Google Earth Engine: Planetary-scale geospatial analysis for everyone N Gorelick, M Hancher, M Dixon, S Ilyushchenko, D Thau, R Moore Remote sensing of Environment 202, 18-27, 2017 | 10943 | 2017 |
An ecoregion-based approach to protecting half the terrestrial realm E Dinerstein, D Olson, A Joshi, C Vynne, ND Burgess, E Wikramanayake, ... BioScience 67 (6), 534-545, 2017 | 1852 | 2017 |
The global distribution and trajectory of tidal flats NJ Murray, SR Phinn, M DeWitt, R Ferrari, R Johnston, MB Lyons, ... Nature 565 (7738), 222-225, 2019 | 769 | 2019 |
Mapping paddy rice planting area in northeastern Asia with Landsat 8 images, phenology-based algorithm and Google Earth Engine J Dong, X Xiao, MA Menarguez, G Zhang, Y Qin, D Thau, C Biradar, ... Remote sensing of environment 185, 142-154, 2016 | 760 | 2016 |
A scalable satellite-based crop yield mapper DB Lobell, D Thau, C Seifert, E Engle, B Little Remote Sensing of Environment 164, 324-333, 2015 | 558 | 2015 |
Automated cropland mapping of continental Africa using Google Earth Engine cloud computing J Xiong, PS Thenkabail, MK Gumma, P Teluguntla, J Poehnelt, ... ISPRS Journal of Photogrammetry and Remote Sensing 126, 225-244, 2017 | 526 | 2017 |
Distribution and dynamics of mangrove forests of South Asia C Giri, J Long, S Abbas, RM Murali, FM Qamer, B Pengra, D Thau Journal of environmental management 148, 101-111, 2015 | 459 | 2015 |
Wildlife insights: A platform to maximize the potential of camera trap and other passive sensor wildlife data for the planet JA Ahumada, E Fegraus, T Birch, N Flores, R Kays, TG O’Brien, J Palmer, ... Environmental Conservation 47 (1), 1-6, 2020 | 162 | 2020 |
& Kommareddy, A.(2013). High-resolution global maps of 21st-century forest cover change MC Hansen, PV Potapov, R Moore, M Hancher, SA Turubanova, ... Science 342 (6160), 850-853, 0 | 118 | |
Building a better urban picture: Combining day and night remote sensing imagery Q Zhang, B Li, D Thau, R Moore Remote Sensing 7 (9), 11887-11913, 2015 | 94 | 2015 |
EEFlux: A Landsat-based Evapotranspiration mapping tool on the Google Earth Engine RG Allen, C Morton, B Kamble, A Kilic, J Huntington, D Thau, N Gorelick, ... 2015 ASABE/IA Irrigation Symposium: Emerging Technologies for Sustainable …, 2015 | 93 | 2015 |
Lifting the information barriers to address sustainability challenges with data from physical geography and earth observation A Lehmann, R Chaplin-Kramer, M Lacayo, G Giuliani, D Thau, K Koy, ... Sustainability 9 (5), 858, 2017 | 34 | 2017 |
Reasoning about taxonomies in first-order logic D Thau, B Ludäscher Ecological Informatics 2 (3), 195-209, 2007 | 34 | 2007 |
Quantifying fire trends in boreal forests with Landsat time series and self-organized criticality A Kato, D Thau, AT Hudak, GW Meigs, LM Moskal Remote Sensing of Environment 237, 111525, 2020 | 31 | 2020 |
Merging taxonomies under RCC-5 algebraic articulations D Thau, S Bowers, B Ludäscher Proceedings of the 2nd international workshop on Ontologies and information …, 2008 | 28 | 2008 |
Comparison of the automatically calibrated Google Evapotranspiration Application—EEFlux and the manually calibrated METRIC application F Foolad, P Blankenau, A Kilic, RG Allen, JL Huntington, TA Erickson, ... Preprints, 2018 | 26 | 2018 |
Satellites uncover 5 surprising hotspots for tree cover loss R Petersen, N Sizer, M Hansen, P Potapov, D Thau World Resources Institute. Retrieved from http://www. wri. org/blog/2015/09 …, 2015 | 22 | 2015 |
Rapid MODIS-based detection of tree cover loss D Wheeler, B Guzder-Williams, R Petersen, D Thau International journal of applied earth observation and geoinformation 69, 78-87, 2018 | 18 | 2018 |
Data procurement for enabling scientific workflows: On exploring inter-ant parasitism S Bowers, D Thau, R Williams, B Ludäscher Semantic Web and Databases: Second International Workshop, SWDB 2004 …, 2005 | 17 | 2005 |